Page 80 - ESAM-1-4

Engineering Science in
Additive Manufacturing TwinPrint: Dual-arm robotic bioprinting

In this work, we address the latter challenge by advancing 2.2. System description
the automation and integration of the different parts within The TwinPrint System, as the name implies, consists of two
the 3D bioprinting system, with the goal of accelerating the identical 3D bioprinting sets; a set is composed of a 3D
technology’s overall progress. printing robotic arm and a microfluidic-based extrusion
Consequently, in this paper, we propose a dual- system, as depicted in Figure 1. Previous studies have
arm, microfluidic extrusion-based multi-material 3D described our 3D bioprinter at length. 20,23,24 In a single print
bioprinter, called TwinPrint, with an integrated graphical job, the sets take turns in printing with different materials,
user interface (GUI). TwinPrint leverages the advantages constituting a multi-material structure. Before printing, the
of robotic arms to develop a system catering to soft robotic arms agree on a start point from which each robot
matter bioinks, including peptide hydrogels, to achieve calculates its movements with respect to this point. A GUI
3D bioprinting of multi-material, geometrically complex Software is built using Python to control and integrate
bio-constructs for skin grafting, disease models, and drug the system’s different components from a single software
testing applications. Taking user workflow into account, platform. The system input is a G-code (Geometry Code)
an intuitive GUI is developed in a pre-, intra-, and post- file of a desired construct, from which the required data
printing layout for quick navigation. Moreover, several are extracted and transmitted to the robots for command
tests to evaluate the system performance, printability, execution. As G-code is designed to contain information
biocompatibility, and cell viability are performed. for Cartesian systems, it first needs to be converted to polar
coordinates for it to be understandable by the robots.
To the best of our knowledge, this is the first work of
its kind that presents synchronized dual robotic arms for 2.2.1. Geometry code (G-code) obtainment
3D bioprinting, free from any crosslinking dependencies
that could further complicate the printing process and 3D bioprinting is an additive manufacturing process that
present potential harm to cell viability. More importantly, uses a computer-aided design (CAD) model, which is
converted into an standard template library (STL) file to
the demonstration of layer-by-layer switching of robotic define the 3D geometry of the object as a mesh of small
arms is an advantageous time saver as compared to a linear 35,36
Cartesian system with a head switching mechanism. Given triangles. Conventionally, the first step in printing is to
load a desired STL file into the printing software and slice it
the fragile nature of cell viability in the bioprinting process, into G-code, which denotes the required XYZ movements
quicker standardized protocols are extremely crucial in and speeds at each coordinate to print the 3D object layer
realizing realistic goals of clinical bioprinting. Finally, the by layer. To this effect, basic objects were designed in
37
capability of increasing degrees of freedom in a robotic arm Solidworks CAD software (Dassault Systèmes, France),
®
setup adds further time, space, and structural complexity including cuboids and rings, and sliced to obtain their
advantages that are far from possible with state-of-the-art G-codes. However, because robots are designed with
Cartesian printers.

2. Materials and methods
2.1. Peptide synthesis

Peptide Ac-Ile-Val-Cha-Lys-NH (IVZK) was synthesized
2
using the solid-phase peptide synthesis method on
a CS136X peptide synthesizer (CSBio, USA). After
synthesis, the peptide was removed from the resin using
a mixture of 95% trifluoroacetic acid, 2.5% tri-isopropyl
silane, and 2.5% water at room temperature for 2 h. The
peptide was then precipitated by adding cold diethyl ether
to the peptide solution and kept overnight at 4°C. The
precipitated peptide was separated from the supernatant
by centrifugation. Finally, the peptide was purified by
reverse-phase high-performance liquid chromatography
with a C-18 column (2–98% acetonitrile in 15 min) at a
flow rate of 20 mL/min and collected at a yield of over 60%.
The peptides were stored within sealed Falcon containers Figure 1. An illustration of the TwinPrint system
at −80°C, and peptide aliquots were taken for experiments. Abbreviation: GUI: Graphical user interface.

Volume 1 Issue 4 (2025) 3 doi: 10.36922/ESAM025410025